Mathematical elements for computer graphics (2nd ed.)
Mathematical elements for computer graphics (2nd ed.)
Computer Vision and Image Processing: A Practical Approach Using Cviptools with Cdrom
Computer Vision and Image Processing: A Practical Approach Using Cviptools with Cdrom
Principles of 3d Image Analysis and Synthesis
Principles of 3d Image Analysis and Synthesis
Detection of linear objects in GPR data
Signal Processing
A tele collaborative surgery framework for 3D heart model
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
Detection of buried landmines using the possibilistic correlation-dependent fusion methods
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
Novel approach for 3-D reconstruction of coronary arteries from two uncalibrated angiographic images
IEEE Transactions on Image Processing
Opti-acoustic stereo imaging: on system calibration and 3-D target reconstruction
IEEE Transactions on Image Processing
Reconstruction of sculpture from its profiles with unknown camera positions
IEEE Transactions on Image Processing
3-D reconstruction of 2-D crystals in real space
IEEE Transactions on Image Processing
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The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. In many fields demand for visualizing objects scanned as cross sectional slices is growing. This research has many real world applications, such as robotic environments, medicine, remote sensing, inspection of industrial parts and geology. An even better way is to visualize the underground object by reconstruction a threedimensional model of those objects from the slices. Objects here are stable underground while, camera is moving. The task of object track in a cross sectional slices consists of two parts: first gather information on changes between succeeding slices (object detection), and second process this information appropriately to obtain the track of an object. If the object is like cable or pipe. The proposed method starts with two dimensional 2D image preprocessing for each slice. The preprocessing involves multispectral to gray conversion, contrast enhancement, segmenting, thresholding and denoising to modify each 2D image slice individually. Preprocessing algorithms involved in this paper are chosen appropriately to have image without noise, with object detected and with object eliminated. After a preprocessing step the proposed algorithm for object detection starts with objects contour finding in each slice, 2D objects transparency and transformation. The last step is the proposed interpolation technique to build the successive slices until the spaces is filled to find out the embedded object.